We investigate how the application of advanced predictive models could help investors to assess and manage climate risk in their portfolios, contributing to the development of more sustainable and resilient investment practices. We highlight the possible applications of predictive analytics as a key tool in climate finance. It emerges how emerging technologies (blockchain and Artificial Intelligence) can improve transparency, efficiency, and climate risk analysis in sustainable investments. Further lines of research are highlighted, focusing on how investors and portfolio managers can develop strategies to manage the risks associated with climate events and the integration of climate risks into the management of Supply Chain Finance to ensure greater resilience and sustainability.

Ferrara, M., T., Ciano, A., Capriotti e S., Muzzioli. "Machine learning technique to compute climate risk in finance" Working paper, DEMB WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi, 2024. https://doi.org/10.25431/11380_1362074

Machine learning technique to compute climate risk in finance

Capriotti, A.;Muzzioli, S.
2024

Abstract

We investigate how the application of advanced predictive models could help investors to assess and manage climate risk in their portfolios, contributing to the development of more sustainable and resilient investment practices. We highlight the possible applications of predictive analytics as a key tool in climate finance. It emerges how emerging technologies (blockchain and Artificial Intelligence) can improve transparency, efficiency, and climate risk analysis in sustainable investments. Further lines of research are highlighted, focusing on how investors and portfolio managers can develop strategies to manage the risks associated with climate events and the integration of climate risks into the management of Supply Chain Finance to ensure greater resilience and sustainability.
2024
Settembre
Inglese
244
Dipartimento di Economia Marco Biagi
ITALIA
Modena
Climate Risk, Machine Learning, Supply Chain Finance, Blockchain, Predictive Models
This work was funded by European Union under the NextGeneration EU Programme within the Plan “PNRR - Missione 4 “Istruzione e Ricerca” - Componente C2 Investimento 1.1 “Fondo per il Programma Nazionale di Ricerca e Progetti di Rilevante Interesse Nazionale (PRIN)” by the Italian Ministry of University and Research (MUR), Project title: “Climate risk and uncertainty: environmental sustainability and asset pricing”. Project code "P20225MJW8" (CUP: E53D23016470001), MUR D.D. financing decree n. 1409 of 14/09/2022. The work was supported also by the University of Modena and Reggio Emilia for the FAR2022 project.
info:eu-repo/semantics/other
Ferrara, M.; Ciano, T.; Capriotti, A.; Muzzioli, S.
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Ferrara, M., T., Ciano, A., Capriotti e S., Muzzioli. "Machine learning technique to compute climate risk in finance" Working paper, DEMB WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi, 2024. https://doi.org/10.25431/11380_1362074
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